The identification of gut neuroendocrine tumor disease by multiple synchronous transcript analysis in blood

NETest® 2.0-A decade of innovation in neuroendocrine tumor diagnostics

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are challenging to diagnose and manage. Because there is a critical need for a reliable biomarker, we previously developed the NETest, a liquid biopsy test that quantifies the expression of 51 neuroendocrine tumor (NET)-specific genes in blood using real-time PCR (NETest 1.0). In this study, we have leveraged our well-established laboratory approach (blood collection, RNA isolation, qPCR) with contemporary supervised machine learning methods and expanded training and testing sets to improve the discrimination and calibration of the NETest algorithm (NETest 2.0). qPCR measurements of RNA-stabilized blood-derived gene expression of 51 NET markers were used to train two supervised classifiers. The first classifier trained on 78 Controls and 162 NETs, distinguishing NETs from controls; the second, trained on 134 stable disease samples, 61 progressive disease samples, differentiated stable from progressive NET disease. In all cases, 80% of data was retained for model training, while remaining 20% were used for performance evaluation. The predictive performance of the AI system was assessed using sensitivity, specificity, and Area under Received Operating Characteristic curves (AUROC). The algorithm with the highest performance was retained for validation in two independent validation sets. Validation Cohort #I consisted of 277 patients and 186 healthy controls from the United States, Latin America, Europe, Africa and Asia, while Validation Cohort #II comprised 291 European patients from the Swiss NET Registry. A specificity cohort of 147 gastrointestinal, pancreatic and lung malignancies (non-NETs) was also evaluated. NETest 2.0 Algorithm #1 (Random Forest/gene expression normalized to ATG4B) achieved an AUROC of 0.91 for distinguishing NETs from controls (Validation Cohort #I), with a sensitivity of 95% and specificity of 81%. In Validation Cohort #II, 92% of NETs with image-positive disease were detected. The AUROC for differentiating NETs from other malignancies was 0.95; the sensitivity was 92% and specificity 90%. NETest 2.0 Algorithm #2 (Random Forest/gene expression normalized to ALG9) demonstrated an AUROC of 0.81 in Validation Cohort #I and 0.82 in Validation Cohort #II for differentiating stable from progressive disease, with specificities of 81% and 82%, respectively. Model performance was not affected by gender, ethnicity or age. Substantial improvements in performance for both algorithms were identified in head-to-head comparisons with NETest 1.0 (diagnostic: p = 1.73 × 10-9; prognostic: p = 1.02 × 10-10). NETest 2.0 exhibited improved diagnostic and prognostic capabilities over NETest 1.0. The assay also demonstrated improved sensitivity for differentiating NETs from other gastrointestinal, pancreatic and lung malignancies. The validation of this tool in geographically diverse cohorts highlights their potential for widespread clinical use.

A blood-based liquid biopsy analyzing soluble immune checkpoints and cytokines identifies distinct neuroendocrine tumors

BACKGROUND

Neuroendocrine neoplasms (NENs) comprise a group of rare tumors originating from neuroendocrine cells, which are present in both endocrine glands and scattered throughout the body. Due to their scarcity and absence of specific markers, diagnosing NENs remains a complex challenge. Therefore, new biomarkers are required, ideally, in easy-to-obtain blood samples.

METHODS

A panel of blood soluble immune checkpoints (sPD-L1, sPD-L2, sPD-1, sCD25, sTIM3, sLAG3, Galectin-9, sCD27, sB7.2 and sSIGLEC5) and cytokines (IL4, IL6, IP10 and MCP1) was quantified in a cohort of 139 NENs, including 29 pituitary NENs, 46 pheochromocytomas and paragangliomas, and 67 gastroenteropancreatic and pulmonary (GEPP) NENs, as well as in 64 healthy volunteers (HVs). The potential of these circulating immunological parameters to distinguish NENs from HVs, differentiate among various NENs subtypes, and predict their prognosis was evaluated using mathematical regression models. These immunological factors-based models generated scores that were evaluated by Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC) analyses. Correlations between these scores and clinical data were performed. From these analyses, a minimal signature emerged, comprising the five shared immunological factors across the models: sCD25, sPD-L2, sTIM3, sLAG3, and Galectin-9. This refined signature was evaluated, validated, and checked for specificity against non-neuroendocrine tumors, demonstrating its potential as a clinically relevant tool for identifying distinct NENs.

RESULTS

Most of the immunological factors analyzed showed specific expression patterns among different NENs. Scores based on signatures of these factors identified NENs with high efficiency, showing AUCs ranging between 0.948 and 0.993 depending on the comparison, and accuracies between 92.52% and 95.74%. These scores illustrated biological features of NENs including the similarity between pheochromocytomas and paragangliomas, the divergence between gastrointestinal and pulmonary NENs, and correlated with clinical features. Furthermore, the models demonstrated strong performance in distinguishing metastatic and exitus GEPP NENs, achieving sensitivities and specificities ranging from 80.95% to 88.89%. Additionally, an easy-to-implement minimal signature successfully identified all analyzed NENs with AUC values exceeding 0.900, and accuracies between 84.11% and 93.12%, which was internally validated by a discovery and validation randomization strategy. These findings highlight the effectiveness of the models and minimal signature in accurately diagnosing and differentiating NENs.

CONCLUSIONS

The analysis of soluble immunological factors in blood presents a promising liquid biopsy approach for identifying NENs, delivering critical insights for both prognosis and diagnosis. This study serves as a proof-of-concept for an innovative clinical tool that holds the potential to transform the management of these rare malignancies, providing a non-invasive and effective method for early detection and disease monitoring.

Developing a peripheral blood RNA-seq based NETseq ensemble classifier: A potential novel tool for non-invasive detection and treatment response assessment in neuroendocrine tumor patients receiving 177Lu-DOTATATE PRRT

Neuroendocrine tumors (NETs) are presented with metastases due to delayed diagnosis. We aimed to identify NET-related biomarkers from peripheral blood. The development and validation of a multi-gene NETseq ensemble classifier using peripheral blood RNA-Seq is reported. RNA-Seq was performed on peripheral blood samples from 178 NET patients and 73 healthy donors. Distinguishing gene features were identified from a learning cohort (59 PRRT-naïve GEP-NET patients and 38 healthy donors). Ensemble classifier combining the output of five machine learning algorithms viz. Random Forest (RF), Extreme Gradient Boosting (XGBOOST), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), and Logistic Regression (LR) were trained and independently validated in the evaluation cohort (n = 106). The response to PRRT was evaluated in the PRRT cohort (n = 46) and the PRRT response monitoring cohort (n = 16). The response to 177Lu-DOTATATE PRRT was assessed using RECIST 1.1 criteria. The Ensemble classifier trained on 61 gene features, distinguished NET from healthy samples with 100% accuracy in the learning cohort. In an evaluation cohort, the classifier achieved 93% sensitivity (95% CI: 87.8%-98.03%) and 91.4% specificity (95% CI: 82.1%-100%) for PRRT-naïve GEP-NETs (AUROC = 95.4%). The classifier returned >87.5% sensitivity across different tumor characteristics and outperformed serum Chromogranin A sensitivity (χ2 = 21.89, p = 4.161e-6). In the PRRT cohort, RECIST 1.1 responders showed significantly lower NETseq prediction scores after 177Lu-DOTATATE PRRT, in comparison to the non-responders. In an independent response monitoring cohort, paired samples (before PRRT and after 2nd or 3rd cycle of PRRT) were analyzed. The NETseq prediction score significantly decreased in partial responders (p = .002) and marginally reduced in stable disease (p = .068). The NETseq ensemble classifier identified PRRT-naïve GEP-NETs with high accuracy (≥92%) and demonstrated a potential role in early treatment response monitoring in the PRRT setting. This blood-based, non-invasive, multi-analyte molecular method could be developed as a valuable adjunct to conventional methods in the detection and treatment response assessment in NET patients.

NETest and Gastro-Entero-Pancreatic Neuroendocrine Tumors: Still Far from Routine Clinical Application? A Systematic Review

Background: Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) are the most prevalent subgroup among NETs and include heterogeneous tumors characterized by different clinical behavior and prognosis. The NETest is a tool based on real-time PCR combined with deep learning strategies to specifically identify tumors with a neuroendocrine genotype. Despite the promising results achieved regarding its utility in the field of GEP-NETs, the NETest has not yet entered into routine clinical practice. Methods: We performed a systematic review aimed at summarizing available evidence on the application of the NETest in both the diagnosis and the prognostic stratification of GEP-NETs. Results: We identified five studies evaluating the diagnostic role of the NETest and nine studies evaluating its prognostic value. The NETest emerged as a reliable biomarker for GEP-NET diagnosis with an accuracy higher than 90%, regardless of tumor stage and grade. However, according to some studies, the NETest showed a low specificity, mainly attributed to interferences with other gastro-intestinal malignancies. In terms of prognostic value, the NETest correlated with the detection of residual disease after surgery in six studies. The NETest was also associated with patients' survival outcomes, namely progression-free survival (PFS) and overall survival (OS) in three studies. Conclusions: According to current systematic review, the value of the NETest both for diagnosis and for prognosis of GEP-NET emerged as robust across different studies. Further prospective analysis on larger GEP-NET series is encouraged to validate this tool, improving patients' diagnosis, management, and follow-up.

A neuroendocrine biomarker revolution from monoanalyte to multianalyte biomarkers in non-functioning gastro-entero-pancreatic neuroendocrine neoplasms

Neuroendocrine neoplasms (NENs) arise from neuroendocrine cells in a wide variety of organs. One of the most affected disease sites is the gastrointestinal system, which originates the gastro-entero-pancreatic NENs (GEP-NENs), a heterogenous group of malignancies that are rapidly increasing in incidence. These tumors can be functioning, with secretory activity leading to identifiable clinical syndromes, or non-functioning, with no secretory activity but with local symptoms of tumor growth and metastasis. A limitation in biomarkers is a crucial unmet need in non-secretory NEN management, as clinical decision-making is made more difficult by obstacles in tumor classification, prognostic evaluation, assessment of treatment response and surveillance. The objective of this review is to present existing and novel biomarkers for NENs that can function as prognostic factors and monitor disease progression or regression longitudinally, with a special emphasis on innovative research into novel multianalyte biomarkers.

Comparative Targeted Genome Profiling between Solid and Liquid Biopsies in Gastroenteropancreatic Neuroendocrine Neoplasms: A Proof-of-Concept Pilot Study

INTRODUCTION

Clinical presentation and genetic profile of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are highly variable, hampering their management. Sequencing of circulating tumor DNA from liquid biopsy (LB) has been proposed as a less invasive alternative to solid biopsy (SB). Our aim was to compare the mutational profile (MP) provided by LB with that deriving from SB in GEP-NETs.

METHODS

SB and LB were derived simultaneously from 6 GEP-NET patients. A comparative targeted next-generation sequencing (NGS) analysis was performed on DNA from SB and LB to evaluate the mutational status of 11 genes (MEN1, DAXX, ATRX, MUTYH, SETD2, DEPDC5, TSC2, ARID1A, CHECK2, MTOR, and PTEN).

RESULTS

Patients (M:F = 2:1; median age 64 years) included 3 with pancreatic and 3 with ileal NETs. NGS detected a median number of 55 variants/sample in SB and 66.5 variants/sample in LB specimens (mutational burden: 0.2-1.9 and 0.3-1.8 mut/Mb, respectively). Missense and nonsense mutations were prevalent in both, mainly represented by C>T transitions. ARID1A, MTOR, and ATRX were consistently mutated in SB, and ARID1A, TSC2, MEN1, PTEN, SETD2, and MUTYH were consistently mutated in LB. DAXX mutations were absent in LB. Seventeen recurrent mutations were shared between SB and LB; in particular, MTOR single-nucleotide variants c.G4731A and c.C2997T were shared by 5 out of 6 patients. Hierarchical clustering supported genetic similarity between SB and LB.

CONCLUSIONS

This pilot study explores the applicability of LB in GEP-NET MP evaluation. Further studies with larger cohorts are needed to validate LB and to define the clinical impact.

The Role of Liquid Biopsy in Gastroenteropancreatic Neuroendocrine Neoplasms

Neuroendocrine neoplasms incidence has been increasing, arising the need for precise and early diagnostic tools. Liquid biopsy (LB) offers a less invasive alternative to tissue biopsy, providing real-time molecular information from circulating tumour components in body fluids. The aim of this review is to analyse the current evidence concerning LB in NENs and its role in clinical practice. We conducted a systematic review in July 2024 focusing on LB applications in NENs, including circulating tumour cells (CTCs), circulating tumour DNA (ctDNA), micro RNA (miRNA), messenger RNA (mRNA) and extracellular vesicles. Sixty-five relevant articles were analysed. The LB showed potential in diagnosing and monitoring NENs. While CTCs face limitations due to low shedding, ctDNA provides valuable information on high-grade neoplasms. MiRNA and mRNA (e.g., the NETest) offer high sensitivity and specificity for diagnosis and prognosis, outperforming traditional markers like chromogranin A. The LB has significant potential for NEN diagnosis and monitoring but lacks widespread clinical integration due to limited prospective studies and guidelines, requiring further validation. Advances in sequencing technologies may enhance the clinical utility of LB in NENs. Future research should focus on refining LB methods, standardising protocols and exploring applications in high-grade NENs.

Genomic Landscape of Pancreatic Neuroendocrine Tumors and Implications for Clinical Practice

Pancreatic neuroendocrine tumors (pNETs) are the second most prevalent neoplasms of the pancreas with variable prognosis and clinical course. Our knowledge of the genetic alterations in patients with pNETs has expanded in the past decade with the availability of whole-genome sequencing and germline testing. This review will focus on potential clinical applications of the genetic testing in patients with pNETs. For somatic testing, we discuss the commonly prevalent somatic mutations and their impact on prognosis and treatment of patients with pNET. We also highlight the relevant genomic biomarkers that predict response to specific treatments. Previously, germline testing was only recommended for high-risk patients with syndromic features (MEN1, VHL, TSC, and NF1), we review the evolving paradigm of germline testing in pNETs as recent studies have now shown that sporadic-appearing pNETs can also harbor germline variants.

Surgical Management and Long-Term Evaluation of Pancreatic Neuroendocrine Tumors

Pancreatic neuroendocrine tumors (PNETs) arise from neuroendocrine cells and are a rare class of heterogenous tumors with increasing incidence. The diagnosis, staging, treatment, and prognosis of PNETs depend heavily on identifying the histologic features and biological mechanisms. Here, the authors provide an overview of the diagnostic workup (biomarkers and imaging), grade, and staging of PNETs. The authors also explore associated genetic mutations and molecular pathways and describe updated guidelines on surgical and systemic treatment modalities.

Evaluation of a blood miRNA/mRNA signature to follow-up Lu-PRRT therapy for G1/G2 intestinal neuroendocrine tumors

Background

177Lu-oxodotreotide peptide receptor therapy (LuPRRT) is an efficient treatment for midgut neuroendocrine tumors (NETs) of variable radiological response. Several clinical, biological, and imaging parameters may be used to establish a relative disease prognosis but none is able to predict early efficacy or toxicities. We investigated expression levels for mRNA and miRNA involved in radiosensitivity and tumor progression searching for correlations related to patient outcome during LuPRRT therapy.

Methods

Thirty-five patients received LuPRRT for G1/G2 midgut NETs between May 2019 and September 2021. Peripheral blood samples were collected prior to irradiation, before and 48 h after the second and the fourth LuPRRT, and at 6-month follow-up. Multiple regression analyses and Pearson correlations were performed to identify the miRNA/mRNA signature that will best predict response to LuPRRT.

Results

Focusing on four mRNAs and three miRNAs, we identified a miRNA/mRNA signature enabling the early identification of responders to LuPRRT with significant reduced miRNA/mRNA expression after the first LuPRRT administration for patients with progressive disease at 1 year (p < 0.001). The relevance of this signature was reinforced by studying its evolution up to 6 months post-LuPRRT. Moreover, nadir absolute lymphocyte count within the first 2 months after the first LuPRRT administration was significantly related to low miRNA/mRNA expression level (p < 0.05) for patients with progressive disease.

Conclusion

We present a pilot study exploring a miRNA/mRNA signature that correlates with early hematologic toxicity and therapeutic response 12 months following LuPRRT. This signature will be tested prospectively in a larger series of patients.

Prioritization of Fluorescence In Situ Hybridization (FISH) Probes for Differentiating Primary Sites of Neuroendocrine Tumors with Machine Learning

Determining neuroendocrine tumor (NET) primary sites is pivotal for patient care as pancreatic NETs (pNETs) and small bowel NETs (sbNETs) have distinct treatment approaches. The diagnostic power and prioritization of fluorescence in situ hybridization (FISH) assay biomarkers for establishing primary sites has not been thoroughly investigated using machine learning (ML) techniques. We trained ML models on FISH assay metrics from 85 sbNET and 59 pNET samples for primary site prediction. Exploring multiple methods for imputing missing data, the impute-by-median dataset coupled with a support vector machine model achieved the highest classification accuracy of 93.1% on a held-out test set, with the top importance variables originating from the ERBB2 FISH probe. Due to the greater interpretability of decision tree (DT) models, we fit DT models to ten dataset splits, achieving optimal performance with k-nearest neighbor (KNN) imputed data and a transformation to single categorical biomarker probe variables, with a mean accuracy of 81.4%, on held-out test sets. ERBB2 and MET variables ranked as top-performing features in 9 of 10 DT models and the full dataset model. These findings offer probabilistic guidance for FISH testing, emphasizing the prioritization of the ERBB2, SMAD4, and CDKN2A FISH probes in diagnosing NET primary sites.

The Quest for Circulating Biomarkers in Neuroendocrine Neoplasms: a Clinical Perspective

OPINION STATEMENT

Given the considerable heterogeneity in neuroendocrine neoplasms (NENs), it appears unlikely that a sole biomarker exists capable of fully capturing all useful clinical aspects of these tumors. This is reflected in the abundant number of biomarkers presently available for the diagnosis, prognosis, and monitoring of NEN patients. Although assessment of immunohistochemical and radiological markers remains paramount and often obligatory, there has been a notable surge of interest in circulating biomarkers over the years given the numerous benefits associated with liquid biopsies. Currently, the clinic primarily relies on single-analyte assays such as the chromogranin A assay, but these are far from ideal because of limitations such as compromised sensitivity and specificity as well as a lack of standardization. Consequently, the quest for NEN biomarkers continued with the exploration of multianalyte markers, exemplified by the development of the NETest and ctDNA-based analysis. Here, an extensive panel of markers is simultaneously evaluated to identify distinct signatures that could enhance the accuracy of patient diagnosis, prognosis determination, and response to therapy prediction and monitoring. Given the promising results, the development and implementation of these multianalyte markers are expected to usher in a new era of NEN biomarkers in the clinic. In this review, we will outline both clinically implemented and more experimental circulating markers to provide an update on developments in this rapidly evolving field.

Monitoring and Surveillance of Patients with Gastroenteropancreatic Neuroendocrine Tumors Undergoing Radioligand Therapy

Radioligand therapy (RLT) with [177Lu]Lu-DOTA-TATE is a standard of care for adult patients with somatostatin-receptor (SSTR)-positive gastroenteropancreatic neuroendocrine tumors (GEP-NETs). Taking advantage of this precision nuclear medicine approach requires diligent monitoring and surveillance, from the use of diagnostic SSTR-targeted radioligand imaging for the selection of patients through treatment and assessments of response. Published evidence-based guidelines assist the multidisciplinary healthcare team by providing acceptable approaches to care; however, the sheer heterogeneity of GEP-NETs can make these frameworks difficult to apply in individual clinical circumstances. There are also contradictions in the literature regarding the utility of novel approaches in monitoring and surveilling patients with GEP-NETs receiving RLT. This article discusses the emerging evidence on imaging, clinical biochemistry, and tumor assessment criteria in the management of patients receiving RLT for GEP-NETs; additionally, it documents our own best practices. This allows us to offer practical guidance on how to effectively implement monitoring and surveillance measures to aid patient-tailored clinical decision-making.

Established and novel circulating neuroendocrine tumor biomarkers for diagnostic, predictive and prognostic use

The management of neuroendocrine tumors (NETs) represents a clinical challenge due to heterogeneity of their clinical behaviour, molecular biology and response to treatment. Over the years, several circulating biomarkers have been developed for the early diagnosis and follow-up of NETs. The specific secretory products of tumors associated with a secretory syndrome (functioning tumors) may be used as diagnostic and/or prognostic biomarkers while the most common non-specific circulating biomarkers, that may be increased in both functioning and non-functioning tumors, are chromogranin A and the neuron specific enolase. However, the diagnostic accuracy as well as the prognostic and predictive value of these biomarkers are limited and novel techniques of multianalyte analysis of regulators of tumor biology have been developed. The NETest has been most extensively studied and proved to be useful in NET diagnosis, early detection of post-operative recurrence and prediction of response to treatment but further investigation establishing higher level of evidence is required for implementation in clinical practice.

An Overview of Circulating Biomarkers in Neuroendocrine Neoplasms: A Clinical Guide

Neuroendocrine neoplasms (NENs) are a heterogeneous group of diseases that are characterized by different behavior and clinical manifestations. The diagnosis and management of this group of tumors are challenging due to tumor complexity and lack of precise and widely validated biomarkers. Indeed, the current circulating mono-analyte biomarkers (such as chromogranin A) are ineffective in describing such complex tumors due to their poor sensitivity and specificity. In contrast, multi-analytical circulating biomarkers (including NETest) are emerging as more effective tools to determine the real-time profile of the disease, both in terms of accurate diagnosis and effective treatment. In this review, we will analyze the capabilities and limitations of different circulating biomarkers focusing on three relevant questions: (1) accurate and early diagnosis; (2) monitoring of disease progression and response to therapy; and (3) detection of early relapse.

Small Bowel Neuroendocrine Tumors-10-Year Experience of the Ottawa Hospital (TOH)

(1) Aim: The prevalence and incidence of small bowel NETs have increased significantly over the past two decades. This study aims to report the 10-year experience of SB-NET management at a regional cancer center in Canada. (2) Materials and methods: We conducted a retrospective study of the clinical and pathological data of patients diagnosed with biopsy-proven SB-NET at The Ottawa Hospital (TOH), Ottawa, Canada between 2011 and 2021. We report the clinicopathological characteristics of these patients, as well as their outcomes data, including survival rates. (3) Results: Between 2011 and 2021, a total of 177 SB-NET cases were identified with 51% (n = 91) of cases being males. The most common sites of the tumors were the ileum 53% (n = 94), followed by the duodenum 9% (n = 16) and jejunum 7% (n = 12). Approximately 24% (n = 42) of the patients had symptoms for over six months prior to diagnosis and 18% (n = 32) had functioning SB-NET during the course of the disease. The majority of patients had locally advanced or metastatic disease at the time of presentation with stage III, and stage IV representing 42% (n = 75), and 41% (n = 73) respectively. The majority of patients 84% (n = 148) had well-differentiated histology. One hundred twenty patients underwent surgical resection of the primary tumor including 28 patients (16%) with limited metastatic disease. A total of 21 patients (18%) had recurrence after curative surgery. A total of 62 patients (35%) received first-line somatostatin analog (SSA) therapy for unresectable disease and seven patients had PRRT after progression on SSA. Five years OS was 100%, 91%, 97%, and 73% for stages I, II, III, and IV respectively. In univariate analysis, carcinoid symptoms, T stage, and differentiation were significant predictors for worse overall survival, but not RFS. (4) Conclusions: Compared to published historical controls, our study suggests improvement in the 5-year survival rate of SB-NETs over the last 10 years.

Neuroendocrine Tumors: Genomics and Molecular Biomarkers with a Focus on Metastatic Disease

Neuroendocrine tumors (NETs) are considered rare tumors that originate from specialized endocrine cells. Patients often present with metastatic disease at the time of diagnosis, which negatively impacts their quality of life and overall survival. An understanding of the genetic mutations that drive these tumors and the biomarkers used to detect new NET cases is important to identify patients at an earlier disease stage. Elevations in CgA, synaptophysin, and 5-HIAA are most commonly used to identify NETs and assess prognosis; however, new advances in whole genome sequencing and multigenomic blood assays have allowed for a greater understanding of the drivers of NETs and more sensitive and specific tests to diagnose tumors and assess disease response. Treating NET liver metastases is important in managing hormonal or carcinoid symptoms and is imperative to improve patient survival. Treatment for liver-dominant disease is varied; delineating biomarkers that may predict response will allow for better patient stratification.

Neuroendocrine Tumor Therapy Response Assessment

Peptide receptor radionuclide therapy has become an integral part of management of neuroendocrine neoplasms. Gallium-68- and lutetium-177-labeled somatostatin receptor analogues have replaced yttrium-90- and 111-indium-based tracers. Several newer targeted therapies are also being used in clinical and research settings. It is imperative to accurately evaluate the response to these agents. The characteristics of NENs and the response patterns of the targeted therapies make response assessment in this group challenging. This article provides an overview of the strengths and weaknesses of the various biomarkers available for response assessment.

Interim Analysis of a Prospective Validation of 2 Blood-Based Genomic Assessments (PPQ and NETest) to Determine the Clinical Efficacy of 177Lu-DOTATATE in Neuroendocrine Tumors

Reliable biomarkers for neuroendocrine tumor (NET) management during peptide receptor radionuclide therapy (PRRT) are lacking. We validated the role of 2 circulating biomarkers: the PRRT prediction quotient (PPQ) as a predictive marker for response and the NETest as a monitoring biomarker. Furthermore, we evaluated whether tissue-based genetic alterations are effective in predicting progression-free survival (PFS). Methods: Data were prospectively collected on patients at the Memorial Sloan Kettering Cancer Center with 177Lu-DOTATATE-treated somatostatin receptor (SSTR)-positive gastroenteropancreatic and lung NETs (n = 67; median age, 66 y; 52% female; 42% pancreatic, 39% small-bowel; 78% grade 1 or 2). All cases were metastatic (89% liver) and had received 1-8 prior treatments (median, 3), including somatostatin analogs (91%), surgery (55%), or chemotherapy (49%). Treatment response included PFS. According to RECIST, version 1.1, responders had stable disease or a partial response (disease-control rate) and nonresponders had progression. Blood was collected before each cycle and at follow-up. Samples were deidentified and assayed and underwent masked analyses. The gene expression assays included RNA isolation, real-time quantitative polymerase chain reaction, and multialgorithm analyses. The PPQ (positive predicts a responder; negative predicts a nonresponder) at baseline was determined. The NETest (0-100 score) was performed. Statistics were analyzed using Mann-Whitney U testing (2-tailed) or Kaplan-Meier survival testing (PFS). In patients with archival tumor tissue, next-generation sequencing was performed through an institutional platform (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets). Results: Forty-one patients (61%) were responders. PPQ accurately predicted 96% (64/67). The hazard ratio for prediction was 24.4 (95% CI, 8.2-72.5). Twelve-month disease control was 97% for PPQ-positive patients versus 26% for PPQ-negative patients (P < 0.0001). Median progression-free survival was not reached in those predicted to respond (PPQ-positive, n = 40) but was 8 mo in those predicted not to respond (PPQ-negative, n = 27). The NETest result in responders was 67 ± 25 at baseline and significantly (P < 0.05) decreased (-37 ± 44%) at follow-up. The NETest result in nonresponders was 44 ± 23 at baseline and significantly (P < 0.05) increased (+76% ± 56%) at progression. Overall, the NETest changes (increases or decreases) were 90% accurate. Thirty patients underwent next-generation sequencing. Tumors were microsatellite-stable, and the median mutational burden was 1.8. Alterations involved mainly the mTOR/PTEN/TSC pathway (30%). No relationship was associated with PRRT response. Conclusion: Our interim analysis confirmed that PPQ is an accurate predictor of 177Lu-DOTATATE responsiveness (radiosensitivity) and that NETest changes accurately correlated with treatment response. Tissue-based molecular genetic information had little value in PRRT prediction. Blood-based gene signatures may improve the management of patients undergoing 177Lu-DOTATATE by providing information on tumor radiosensitivity and disease course, thus allowing individualized strategies.

Risk Stratification of Pancreatic Neuroendocrine Neoplasms Based on Clinical, Pathological, and Molecular Characteristics

Pancreatic neuroendocrine neoplasms consist of heterogeneous diseases. Depending on the novel features detected by various modern technologies, their classification and related prognosis predictions continue to change and develop. The role of traditional clinicopathological prognostic factors, including classification systems, is also being refined, and several attempts have been made to predict a more accurate prognosis through novel serum biomarkers, genetic factors, and epigenetic factors that have been identified through various state-of-the-art molecular techniques with multiomics sequencing. In this review article, the latest research results including the traditional approach to prognostic factors and recent advanced strategies for risk stratification of pancreatic neuroendocrine neoplasms based on clinical, pathological, and molecular characteristics are summarized. Predicting prognosis through multi-factorial assessments seems to be more efficacious, and prognostic factors through noninvasive methods are expected to develop further advances in liquid biopsy in the future.

NETest: serial liquid biopsies in gastroenteropancreatic NET surveillance

Objective

Up to now, serial NETest measurements in individuals assessing the disease course of gastroenteropancreatic neuroendocrine tumors (GEPNETs) at long-term follow-up and treatment response were not studied.

Design

The study was a longitudinal validation study of serial NETest measurements - a blood-based gene expression signature - in 132 patients with GEPNETs on therapy or watch-and-wait strategy.

Methods

Serial samples were collected during 46 (range: 6-71) months of follow-up. NETest scores were compared with Response Evaluation Criteria in Solid Tumors version 1.1-defined treatment response (e.g. no evidence of disease (NED), stable disease (SD) or progressive disease (PD)).

Results

Consecutive NETest scores fluctuated substantially (range: 0-100) over time in individuals with SD (n = 28) and NED (n = 30). Follow-up samples were significantly higher in SD (samples 3-5) and NED subgroups (samples 2-5) compared with baseline results, without changes in imaging. In 82% of untreated patients with PD, consecutive NETest scores consistently remained high. In patients undergoing systemic treatment, the median pre-treatment NETest score in treatment-responders was 76.5 (n = 22) vs 33 (n = 12) in non-responders (P = 0.001). Patients with low pre-treatment scores had 21 months reduced progression-free survival (10 vs 31 months; P = 0.01). The accuracy of the NETest for treatment response prediction was 0.73 (P = 0.009).

Conclusion

In patients not undergoing treatment, consecutive low NETest scores are associated with indolent behavior. Patients who develop PD exhibit elevated scores. Elevated results have important predictive value for treatment responsiveness and could be used for individualizing decisions on systemic therapy. The clinical value of follow-up NETest scores for patients who choose to watch and wait requires further study.

Update on the clinical management of multiple endocrine neoplasia type 1

This review provides an overview of novel insights in the clinical management of patients with Multiple Endocrine Neoplasia Type 1, focusing on the last decade since the last update of the MEN1 guidelines. With regard to Diagnosis: Mutation-negative patients with 2/3 main manifestations have a different clinical course compared to mutation-positive patients. As for primary hyperparathyroidism: subtotal parathyroidectomy is the initial procedure of choice. Current debate centres around the timing of initial parathyroidectomy as well as the controversial topic of unilateral clearance in young patients. For duodenopancreatic neuroendocrine tumours (NETs), the main challenge is accurate and individualized risk stratification to enable personalized surveillance and treatment. Thymus NETs remain one of the most aggressive MEN1-related tumours. Lung NETs are more frequent than previously thought, generally indolent, but rare aggressive cases do occur. Pituitary adenomas are most often prolactinomas and nonfunctioning microadenomas with an excellent prognosis and good response to therapy. Breast cancer is recognized as part of the MEN1 syndrome in women and periodical screening is advised. Clinically relevant manifestations are already seen at the paediatric age and initiating screening in the second decade is advisable. MEN1 has a significant impact on quality of life and US data show a significant financial burden. In conclusion, patient outcomes have improved, but much is still to be achieved. For care tailored to the needs of the individual patient and improving outcomes on an individual basis, studies are now needed to define predictors of tumour behaviour and effects of more individualized interventions.

Circulating Neuroendocrine Tumor Biomarkers: Past, Present and Future

Neuroendocrine tumors are a heterogeneous group of neoplasms originating from the diffuse endocrine system. Depending on primary location and hormonal status, they range in terms of clinical presentation, prognosis and treatment. Functional tumors often develop symptoms indicating an excess of hormones produced by the neoplasm (exempli gratia insulinoma, glucagonoma and VIPoma) and can be diagnosed using monoanalytes. For non-functional tumors (inactive or producing insignificant amounts of hormones), universal biomarkers have not been established. The matter remains an important unmet need in the field of neuroendocrine tumors. Substances researched over the years, such as chromogranin A and neuron-specific enolase, lack the desired sensitivity and specificity. In recent years, the potential use of Circulating Tumor Cells or multianalytes such as a circulating microRNA and NETest have been widely discussed. They offer superior diagnostic parameters in comparison to traditional biomarkers and depict disease status in a more comprehensive way. Despite a lot of promise, no international standards have yet been developed regarding their routine use and clinical application. In this literature review, we describe the analytes used over the years and cover novel biomarkers that could find a use in the future. We discuss their pros and cons while showcasing recent advances in the field of neuroendocrine tumor biomarkers.

Spatiotemporal heterogeneity and clinical challenge of pancreatic neuroendocrine tumors

During the course of pancreatic neuroendocrine tumors (NETs), they generally become more heterogeneous with individual cells exhibiting distinct molecular fingerprints. This heterogeneity manifests itself through an unequal distribution of genetically-variant, tumor cell subpopulations within disease locations (i.e., spatial heterogeneity) or changes in the genomic landscape over time (i.e., temporal heterogeneity); these characteristics complicate clinical diagnosis and treatment. Effective, feasible tumor heterogeneity detection and eradication methods are essential to overcome the clinical challenges of pancreatic NETs. This review explores the molecular fingerprints of pancreatic NETs and the spectrum of tumoral heterogeneity. We then describe the challenges of assessing heterogeneity by liquid biopsies and imaging modalities and the therapeutic challenges for pancreatic NETs. In general, navigating these challenges, refining approaches for translational research, and ultimately improving patient care are available once we have a better understanding of intratumoral spatiotemporal heterogeneity.

Pancreatic Incidentaloma

Pancreatic incidentalomas (PIs) represent a clinical entity increasingly recognized due to advances in and easier access to imaging techniques. By definition, PIs should be detected during abdominal imaging performed for indications other than a pancreatic disease. They range from small cysts to invasive cancer. The incidental diagnosis of pancreatic cancer can contribute to early diagnosis and treatment. On the other hand, inadequate management of PIs may result in overtreatment and unneeded morbidity. Therefore, there is a strong need to evaluate the nature and clinical features of individual PIs. In this review, we summarize the major characteristics related to PIs and present suggestions for their management.

Know thy tumour: Biomarkers to improve treatment of molecular radionuclide therapy

Molecular radionuclide therapy (MRT) is an effective treatment for both localised and disseminated tumours. Biomarkers can be used to identify potential subtypes of tumours that are known to respond better to standard MRT protocols. These enrolment-based biomarkers can further be used to develop dose-response relationships using image-based dosimetry within these defined subtypes. However, the biological identity of the cancers treated with MRT are commonly not well-defined, particularly for neuroendocrine neoplasms. The biological heterogeneity of such cancers has hindered the establishment of dose-responses and minimum tumour dose thresholds. Biomarkers could also be used to determine normal tissue MRT dose limits and permit greater injected doses of MRT in patients. An alternative approach is to understand the repair capacity limits of tumours using radiobiology-based biomarkers within and outside patient cohorts currently treated with MRT. It is hoped that by knowing more about tumours and how they respond to MRT, biomarkers can provide needed dimensionality to image-based biodosimetry to improve MRT with optimized protocols and personalised therapies.

An update on the diagnosis of gastroenteropancreatic neuroendocrine neoplasms

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) arise from neuroendocrine cells found throughout the gastrointestinal tract and islet cells of the pancreas. The incidence and prevalence of GEP-NENs have been increasing each year due to higher awareness, improved diagnostic modalities, and increased incidental detection on cross-sectional imaging and endoscopy for cancer screening and other conditions and symptoms. GEP-NENs are a heterogeneous group of tumors and have a wide range in clinical presentation, histopathologic features, and molecular biology. Clinical presentation most commonly depends on whether the GEP-NEN secretes an active hormone. The World Health Organization recently updated the classification of GEP-NENs to introduce a distinction between high-grade neuroendocrine tumors and neuroendocrine carcinomas, which can be identified using histology and molecular studies and are more aggressive with a worse prognosis compared to high-grade neuroendocrine tumors. As our understanding of the biology of GEP-NENs has grown, new and improved diagnostic modalities can be developed and optimized. Here, we discuss clinical features and updates in diagnosis, including histopathological analysis, biomarkers, molecular techniques, and radiology of GEP-NENs. We review established diagnostic tests and discuss promising novel diagnostic tests that are currently in development or require further investigation and validation prior to broad utilization in patient care.

New Developments in Gastric Neuroendocrine Neoplasms

Purpose of Review

Gastric neuroendocrine neoplasms (g-NENs) are a rare type of stomach cancer. The three main subtypes have different pathogeneses, biological behaviours and clinical characteristics, so they require different management strategies. This article will provide an overview of g-NENs and highlight recent advances in the field.

Recent Findings

Molecular profiling has revealed differences between indolent and aggressive g-NENs, as well as a new somatic mutation responsible for some familial type I g-NENs. Novel biomarkers have been developed which will hopefully improve diagnosis, treatment, risk stratification and follow-up. Patient treatment is also changing, as evidence supports the use of less aggressive options (e.g. endoscopic surveillance or resection) in some patients with more indolent tumours.

Summary

g-NEN heterogeneity poses challenges in understanding and managing this rare disease. More basic science research is needed to investigate molecular pathogenesis, and future larger clinical studies will hopefully also further improve treatment and patient outcomes.

NETest: A Systematic Review Focusing on the Prognostic and Predictive Role

The NETest is a standardized and reproducible liquid biopsy for neuroendocrine tumors (NETs). It evaluates the expression of 51 NET genes by real-time polymerase chain reaction, providing an accurate molecular profile of the neoplasm. Diagnostic utility of NETest has been widely demonstrated, while its role in predicting prognosis and treatment response is less studied. This systematic review aims to collect and discuss the available evidence on the prognostic and predictive role of NETest, trying to answer 3 questions, frequently raised in clinical practice. Is NETest able to differentiate stable from progressive disease? Increased NETest levels (at least >40%) correlate with disease progression. Is NETest able to predict tumor progression and tumor response to treatment? Some studies demonstrated that the baseline NETest score >33-40% could predict tumor progression. Moreover, NETest performed after treatment (as peptide receptor radionuclide therapy) could predict treatment response also before radiological findings, since the decrease or stability of NETest score predicts tumor response to treatment. Is NETest able to evaluate tumor recurrence risk after surgery? NETest can predict surgical treatment outcome detecting minimal residual disease after radical surgery, which is characterized by a lower but positive NETest score (20-40%), while a higher score (>33-40%) is associated with nonradical surgery. In conclusion, in addition to its demonstrated diagnostic role, this systematic review highlights the efficacy of NETest to assess disease status at the moment of the NETest execution and to predict tumor recurrence after surgery. The efficacy for other applications should be proven by additional studies.

Perspectives on the diagnostic, predictive and prognostic markers of neuroendocrine neoplasms (Review)

Neuroendocrine neoplasms (NENs) are a heterogeneous group of rare tumors with different types of physiology and prognosis. Therefore, prognostic information, including morphological differentiation, grade, tumor stage and primary location, are invaluable and contribute to the formulation of treatment decisions. Biomarkers that are currently used, including chromogranin A (CgA), serotonin and neuron-specific enolase, are singular parameters that cannot be used to accurately predict variables associated with tumor growth, including proliferation, metabolic rate and metastatic potential. In addition, site-specific biomarkers, such as insulin and gastrin, cannot be applied to all types of NENs. The clinical application of broad-spectrum markers, as it is the case for CgA, remains controversial despite being widely used. Due to limitations of the currently available mono-analyte biomarkers, recent studies were conducted to explore novel parameters for NEN diagnosis, prognosis, therapy stratification and evaluation of treatment response. Identification of prognostic factors for predicting NEN outcome is a critical requirement for the planning of adequate clinical management. Advances in ‘liquid’ biopsies and genomic analysis techniques, including microRNA, circulating tumor DNA or circulating tumor cells and sophisticated biomathematical analysis techniques, such as NETest or molecular image-based biomarkers, are currently under investigation as potentially novel tools for the management of NENs in the future. Despite these recent findings yielding promising observations, further research is necessary. The present review therefore summarizes the existing knowledge and recent advancements in the exploration of biochemical markers for NENs, with focus on gastroenteropancreatic-neuroendocrine tumors.

A novel liquid biopsy (NETest) identifies paragangliomas and pheochromocytomas with high accuracy

Pheochromocytomas and paragangliomas (PHEOs/PGLs) represent diagnostically challenging and complex neuroendocrine tumors (NETs). Current biomarker tests for PHEOs/PGLs are technically complex or limited. We assessed the diagnostic utility of a NET-specific 51-marker gene blood assay (NETest) in patients with PHEOs/PGLs (n = 81), including ten pediatric patients, and age-/gender-matched controls (n = 142) using a prospective case:control (1:2) analysis. mRNA was measured (qPCR), and results were scaled from 0 to 100 (upper limit of normal < 20). Receiver operating curve (ROC) and non-parametric (Mann-Whitney) tests were used for analyses (two-tailed). All data are presented as mean ± s.e.m. NETest accuracy for PHEO/PGL diagnosis was 100%. PHEO/PGL scores were 70 ± 3 vs 8.5 ± 1 in controls (P < 0.0001), and ROC analysis was 0.99 ± 0.004 (P < 0.0001). Diagnostic metrics were 94% accurate, 100% sensitive, and 92% specific. Imaging correlation with 68Ga-PET-SSA was 100%. NETest levels in PHEOs (n = 26) were significantly (P < 0.0001) elevated (83 ± 4) vs 66 ± 4 in PGLs (n = 40) and mixed PHEOs/PGLs (n = 5: 37 ± 3). Adrenal-derived tumors (n = 30) exhibited higher scores (76 ± 5) than extra-adrenal-derived tumors (66 ± 4, P < 0.05). Cluster 2 tumors exhibited significantly (P = 0.034) elevated NETest levels (n = 4: 92 ± 2) vs cluster 1 tumors (n = 35: 69 ± 4). Regulatory pathway analysis identified elevated RAS-RAF, metastatic, pluripotential, neural and secretory gene cluster levels (P < 0.05) in PHEOs compared to PGLs. Cluster 2 PPGLs exhibited elevated (P = 0.046) levels of growth factor signaling genes compared to cluster 1. The PHEOs/PGLs in the pediatric cohort (n = 10) were all NETest-positive (81 ± 8) and exhibited a gene expression profile spectrum analogous to adults. Circulating NET transcript analysis identifies PHEOs/PGLs with 100% efficacy and is likely to have clinical utility in the diagnosis and management of PHEO/PGL patients.

Treatment of advanced gastroenteropancreatic neuroendocrine neoplasia, are we on the way to personalised medicine?

Gastroenteropancreatic neuroendocrine neoplasia (GEPNEN) comprises clinically as well as prognostically diverse tumour entities often diagnosed at late stage. Current classification provides a uniform terminology and a Ki67-based grading system, thereby facilitating management. Advances in the study of genomic and epigenetic landscapes have amplified knowledge of tumour biology and enhanced identification of prognostic and potentially predictive treatment subgroups. Translation of this genomic and mechanistic biology into advanced GEPNEN management is limited. 'Targeted' treatments such as somatostatin analogues, peptide receptor radiotherapy, tyrosine kinase inhibitors and mammalian target of rapamycin inhibitors are treatment options but predictive tools are lacking. The inability to identify clonal heterogeneity and define critical oncoregulatory pathways prior to therapy, restrict therapeutic efficacy as does the inability to monitor disease status in real time. Chemotherapy in the poor prognosis NEN G3 group, though associated with acceptable response rates, only leads to short-term tumour control and their molecular biology requires delineation to provide new and more specific treatment options.The future requires an exploration of the NEN tumour genome, its microenvironment and an identification of critical oncologic checkpoints for precise drug targeting. In the advance to personalised medical treatment of patients with GEPNEN, clinical trials need to be based on mechanistic and multidimensional characterisation of each tumour in order to identify the therapeutic agent effective for the individual tumour.This review surveys advances in NEN research and delineates the current status of translation with a view to laying the basis for a genome-based personalised medicine management of advanced GEPNEN.

A multigenomic liquid biopsy biomarker for neuroendocrine tumor disease outperforms CgA and has surgical and clinical utility

BACKGROUND

Biomarkers are key tools in cancer management. In neuroendocrine tumors (NETs), Chromogranin A (CgA) was considered acceptable as a biomarker. We compared the clinical efficacy of a multigenomic blood biomarker (NETest) to CgA over a 5-year period.

PATIENTS AND METHODS

An observational, prospective, cross-sectional, multicenter, multinational, comparative cohort assessment. Cohort 1: NETest evaluation in NETs (n = 1684) and cancers, benign diseases, controls (n = 731). Cohort 2: (n = 1270): matched analysis of NETest/CgA in a sub-cohort of NETs (n = 922) versus other diseases and controls (n = 348). Disease status was assessed by response evaluation criteria in solid tumors (RECIST). NETest measurement: qPCR [upper limit of normal (ULN: 20)], CgA (EuroDiagnostica, ULN: 108 ng/ml).

STATISTICS

Mann-Whitney U-test, AUROC, chi-square and McNemar' test.

RESULTS

Cohort 1: NETest diagnostic accuracy was 91% (P < 0.0001) and identified pheochromocytomas (98%), small intestine (94%), pancreas (91%), lung (88%), gastric (80%) and appendix (79%). NETest reflected grading: G1: 40 ± 1, G2 (50 ± 1) and G3 (52 ± 1). Locoregional disease levels were lower (38 ± 1) than metastatic (52 ± 1, P < 0.0001). NETest accurately stratified RECIST-assessed disease extent: no disease (21 ± 1), stable (43 ± 2), progressive (62 ± 2) (P < 0.0001). NETest concordance with imaging (CT/MRI/⁶⁸Ga-SSA-PET) 91%. Presurgery, all NETs (n = 153) were positive (100%). After palliative R1/R2 surgery (n = 51) all (100%) remained elevated. After curative R0-surgery (n = 102), NETest levels were normal in 81 (70%) with no recurrence at 2 years. In the 31 (30%) with elevated levels, 25 (81%) recurred within 2 years. Cohort #2: NETest diagnostic accuracy was 87% and CgA 54% (P < 0.0001). NETest was more accurate than CgA for grading (chi-square = 7.7, OR = 18.5) and metastatic identification (chi-square = 180, OR = 8.4). NETest identified progressive disease (95%) versus CgA (57%, P < 0.0001). Imaging concordance for NETest was 91% versus CgA (46%) (P < 0.0001). Recurrence prediction after surgery was NETest-positive in >94% versus CgA 11%.

CONCLUSION

NETest accurately diagnoses NETs and is an effective surrogate marker for imaging, grade, metastases and disease status compared to CgA. A multigenomic liquid biopsy is an accurate biomarker of NET disease.

Circulating MicroRNAs in Small-bowel Neuroendocrine Tumors: A Potential Tool for Diagnosis and Assessment of Effectiveness of Surgical Resection

OBJECTIVE

To discover serum-based microRNA (miRNA) biomarkers for small-bowel neuroendocrine tumors (SBNET) to help guide clinical decisions.

BACKGROUND

MiRNAs are small noncoding RNA molecules implicated in the initiation and progression of many cancers. MiRNAs are remarkably stable in bodily fluids, and can potentially be translated into clinically useful biomarkers. Novel biomarkers are needed in SBNET to determine disease aggressiveness, select patients for treatment, detect early recurrence, and monitor response.

METHODS

This study was performed in 3 stages (discovery, validation, and a prospective, longitudinal assessment). Discovery comprised of global profiling of 376 miRNA in sera from SBNET patients (n = 11) versus healthy controls (HCs; n = 3). Up-regulated miRNAs were subsequently validated in additional SBNET (n = 33) and HC sera (n = 14); and then longitudinally after SBNET resection (n = 12), with serial serum sampling (preoperatively day 0; postoperatively at 1 week, 1 month, and 12 months).

RESULTS

Four serum miRNAs (miR-125b-5p, -362-5p, -425-5p and -500a-5p) were significantly up-regulated in SBNET (P < 0.05; fold-change >2) based on multiple normalization strategies, and were validated by RT-qPCR. This combination was able to differentiate SBNET from HC with an area under the curve of 0.951. Longitudinal assessment revealed that miR-125b-5p returned towards HC levels at 1 month postoperatively in patients without disease, whereas remaining up-regulated in those with residual disease (RSD). This was also true at 12 months postoperatively. In addition, miR-362-5p appeared up-regulated at 12 months in RSD and recurrent disease (RCD).

CONCLUSIONS

Our study represents the largest global profiling of serum miRNAs in SBNET patients, and the first to evaluate ongoing serum miRNA expression changes after surgical resection. Serum miR-125b-5p and miR-362-5p have potential to be used to detect RSD/RCD.

Multiple endocrine neoplasia type 1 (MEN-1) and neuroendocrine neoplasms (NENs)

Neuroendocrine neoplasms (NENs) are relatively rare neoplasms with 6.4-times increasing age-adjusted annual incidence during the last four decades. NENs arise from neuroendocrine cells, which release hormones in response to neuronal stimuli and they are distributed into organs and tissues. The presentation and biological behaviour of the NENs are highly heterogeneous, depending on the organ. The increased incidence is mainly due to increased awareness and improved detection methods both in the majority of sporadic NENs (non-inherited), but also the inherited groups of neoplasms appearing in at least ten genetic syndromes. The most important one is multiple endocrine neoplasia type 1 (MEN-1), caused by mutations in the tumour suppressor gene MEN1. MEN-1 has been associated with different tumour manifestations of NENs e.g. pancreas, gastrointestinal tract, lungs, thymus and pituitary. Pancreatic NENs tend to be less aggressive when arising in the setting of MEN-1 compared to sporadic pancreatic NENs. There have been very important improvements over the past years in both genotyping, genetic counselling and family screening, introduction and validation of various relevant biomarkers, as well as newer imaging modalities. Alongside this development, both medical, surgical and radionuclide treatments have also advanced and improved morbidity, quality of life and mortality in many of these patients. Despite this progress, there is still space for improving insight into the genetic and epigenetic factors in relation to the biological mechanisms determining NENs as part of MEN-1. This review gives a comprehensive update of current evidence for co-occurrence, diagnosis and treatment of MEN-1 and neuroendocrine neoplasms and highlight the important progress now finding its way to international guidelines in order to improve the global management of these patients.

Treatment personalization in gastrointestinal neuroendocrine tumors

The clinical scenario of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) is continuously changing due to significant improvements in the definition of their molecular landscapes and the introduction of innovative therapeutic approaches. Many efforts are currently employed in the integration of the genetics/epigenetics and clinical information. This is leading to an improvement of tumor classification, prognostic stratification and ameliorating the management of patients based on a personalized approach.

A Plasma Protein Biomarker Strategy for Detection of Small Intestinal Neuroendocrine Tumors

BACKGROUND

Small intestinal neuroendocrine tumors (SI-NETs) are difficult to diagnose in the early stage of disease. Current blood biomarkers such as chromogranin A (CgA) and 5-hydroxyindolacetic acid have low sensitivity (SEN) and specificity (SPE). This is a first preplanned interim analysis (Nordic non-interventional, prospective, exploratory, EXPLAIN study [NCT02630654]). Its objective is to investigate if a plasma protein multi-biomarker strategy can improve diagnostic accuracy (ACC) in SI-NETs.

METHODS

At the time of diagnosis, before any disease-specific treatment was initiated, blood was collected from patients with advanced SI-NETs and 92 putative cancer-related plasma proteins from 135 patients were analyzed and compared with the results of age- and sex-matched controls (n = 143), using multiplex proximity extension assay and machine learning techniques.

RESULTS

Using a random forest model including 12 top ranked plasma proteins in patients with SI-NETs, the multi-biomarker strategy showed SEN and SPE of 89 and 91%, respectively, with negative predictive value (NPV) and positive predictive value (PPV) of 90 and 91%, respectively, to identify patients with regional or metastatic disease with an area under the receiver operator characteristic curve (AUROC) of 99%. In 30 patients with normal CgA concentrations, the model provided a diagnostic SPE of 98%, SEN of 56%, and NPV 90%, PPV of 90%, and AUROC 97%, regardless of proton pump inhibitor intake.

CONCLUSION

This interim analysis demonstrates that a multi-biomarker/machine learning strategy improves diagnostic ACC of patients with SI-NET at the time of diagnosis, especially in patients with normal CgA levels. The results indicate that this multi-biomarker strategy can be useful for early detection of SI-NETs at presentation and conceivably detect recurrence after radical primary resection.

NETest is superior to chromogranin A in neuroendocrine neoplasia: a prospective ENETS CoE analysis

INTRODUCTION

The absence of a reliable, universal biomarker is a significant limitation in neuroendocrine neoplasia (NEN) management. We prospectively evaluated two CgA assays, (NEOLISA, EuroDiagnostica) and (CgA ELISA, Demeditec Diagnostics (DD)) and compared the results to the NETest.

METHODS

NEN cohort (n = 258): pancreatic, n = 67; small intestine, n = 40; appendiceal, n = 10; rectal, n = 45; duodenal, n = 9; gastric, n = 44; lung, n = 43. Image-positive disease (IPD) (n = 123), image & histology- negative (IND) (n = 106), and image-negative and histology positive (n = 29). CgA metrics: NEOLISA, ULN: 108 ng/mL, DD: ULN: 99 ng/mL. Data mean ± s.e.m. NETest: qRT-PCR - multianalyte analyses, ULN: 20. All samples de-identified and assessed blinded. Statistics: Mann-Whitney U-test, Pearson correlation and McNemar-test.

RESULTS

CgA positive in 53/258 (NEOLISA), 32 (DD) and NETest-positive in 157/258. In image- positive disease (IPD, n = 123), NEOLISA-positive: 33% and DD: 19%. NETest-positive: 122/123 (99%; McNemar's Chi2= 79-97, P < 0.0001). NEOLISA was more accurate than DD (P = 0.0003). In image- negative disease (IND), CgA was NEOLISA-positive (11%), DD (8%), P = NS, and NETest (33%). CgA assays could not distinguish progressive (PD) from stable disease (SD) or localized from metastatic disease (MD). NETest was significantly higher in PD (47 ± 5) than SD (29 ± 1, P = 0.0009). NETest levels in MD (35 ± 2) were elevated vs localized disease (24 ± 1.3, P = 0.008).

CONCLUSIONS

NETest, a multigenomic mRNA biomarker, was ~99% accurate in the identification of NEN disease. The CgA assays detected NEN disease in 19-33%. Multigenomic blood analysis using NETest is more accurate than CgA and should be considered the biomarker standard of care.

Blood Molecular Genomic Analysis Predicts the Disease Course of Gastroenteropancreatic Neuroendocrine Tumor Patients: A Validation Study of the Predictive Value of the NETest®

Reliable prediction of disease status is a major challenge in managing gastroenteropancreatic neuroendocrine tumors (GEP-NETs). The aim of the study was to validate the NETest®, a blood molecular genomic analysis, for predicting the course of disease in individual patients compared to chromogranin A (CgA). NETest® score (normal ≤20%) and CgA level (normal <100 µg/L) were measured in 152 GEP-NETs. The median follow-up was 36 (4-56) months. Progression-free survival was blindly assessed (Response Evaluation Criteria in Solid Tumors [RECIST] version 1.1). Optimal cutoffs (area under the receiver operating characteristic curve [AUC]), odds ratios, as well as negative and positive predictive values (NPVs/PPVs) were calculated for predicting stable disease (SD) and progressive disease (PD). Of the 152 GEP-NETs, 86% were NETest®-positive and 52% CgA-positive. -NETest® AUC was 0.78 versus CgA 0.73 (p = ns). The optimal cutoffs for predicting SD/PD were 33% for the NETest® and 140 µg/L for CgA. Multivariate analyses identified NETest® as the strongest predictor for PD (odds ratio: 5.7 [score: 34-79%]; 12.6 [score: ≥80%]) compared to CgA (odds ratio: 3.0), tumor grade (odds ratio: 3.1), or liver metastasis (odds ratio: 7.7). The NETest® NPV for SD was 87% at 12 months. The PPV for PD was 47 and 64% (scores 34-79% and ≥80%, respectively). NETest® metrics were comparable in the watchful waiting, treatment, and no evidence of disease (NED) subgroups. For CgA (>140 ng/mL), NPV and PPV were 83 and 52%. CgA could not predict PD in the watchful waiting or NED subgroups. The NETest® reliably predicted SD and was the strongest predictor of PD. CgA had lower utility. The -NETest® anticipates RECIST-defined disease status up to 1 year before imaging alterations are apparent.

Prospective Evaluation of the NETest as a Liquid Biopsy for Gastroenteropancreatic and Bronchopulmonary Neuroendocrine Tumors: An ENETS Center of Excellence Experience

BACKGROUND

There is a substantial unmet clinical need for an accurate and effective blood biomarker for neuroendocrine neoplasms (NEN). We therefore evaluated, under real-world conditions in an ENETS Center of Excellence (CoE), the clinical utility of the NETest as a liquid biopsy and compared its utility with chromogranin A (CgA) measurement.

METHODS

The cohorts were: gastroenteropancreatic NEN (GEP-NEN; n = 253), bronchopulmonary NEN (BPNEN; n = 64), thymic NEN (n = 1), colon cancer (n = 37), non-small-cell lung cancer (NSCLC; n = 63), benign lung disease (n = 59), and controls (n = 86). In the GEPNEN group, 164 (65%) had image-positive disease (IPD, n = 135) or were image-negative but resection-margin/biopsy-positive (n = 29), and were graded as G1 (n = 106), G2 (n = 49), G3 (n = 7), or no data (n = 2). The remainder (n = 71) had no evidence of disease (NED). In the BPNEN group, 43/64 (67%) had IPD. Histology revealed typical carcinoids (TC, n = 14), atypical carcinoids (AC, n = 14), small-cell lung cancer (SCLC, n = 11), and large-cell neuroendocrine carcinoma (LCNEC, n = 4). Disease status (stable or progressive) was evaluated according to RECIST v1.1. Blood sampling involved NETest (n = 563) and NETest/CgA analysis matched samples (n = 178). NETest was performed by PCR (on a scale of 0-100), with a score ≥20 reflecting a disease-positive status and >40 reflecting progressive disease. CgA positivity was determined by ELISA. Samples were deidentified and measurements blinded. The Kruskal-Wallis, Mann-Whitney U, and McNemar tests, and the area under the curve (AUC) of the receiver-operating characteristics (ROC) were used in the statistical analysis.

RESULTS

In the GEPNEN group, NETest was significantly higher (34.4 ± 1.8, p < 0.0001) in disease-positive patients than in patients with NED (10.5 ± 1, p < 0.0001), colon cancer patients (18 ± 4, p < 0.0004), and controls (7 ± 0.5, p < 0.0001). Sensitivity for detecting disease compared to controls was 89% and specificity was 94%. NETest levels were increased in G2 vs. G1 (39 ± 3 vs. 32 ± 2, p = 0.02) and correlated with stage (localized: 26 ± 2 vs. regional/distant: 40 ± 3, p = 0.0002) and progression (55 ± 5 vs. 34 ± 2 in stable disease, p = 0.0005). In the BPNEN group, diagnostic sensitivity was 100% and levels were significantly higher in patients with bronchopulmonary carcinoids (BPC; 30 ± 1.3) who had IPD than in controls (7 ± 0.5, p < 0.0001), patients with NED (24.1 ± 1.3, p < 0.005), and NSCLC patients (17 ± 3, p = 0.0001). NETest levels were higher in patients with poorly differentiated BPNEN (LCNEC + SCLC; 59 ± 7) than in those with BPC (30 ± 1.3, p = 0.0005) or progressive disease (57.8 ± 7), compared to those with stable disease (29.4 ± 1, p < 0.0001). The AUC for differentiating disease from controls was 0.87 in the GEPNEN group and 0.99 in BPC patients (p < 0.0001). Matched CgA analysis was performed in 178 patients. In the GEPNEN group (n = 135), NETest was significantly more accurate for detecting disease (99%) than CgA positivity (53%; McNemar test χ2 = 87, p < 0.0001). In the BPNEN group (n = 43), NETest was significantly more accurate for disease detection (100%) than CgA positivity (26%; McNemar's test χ2 = 30, p < 0.0001).

CONCLUSIONS

The NETest is an accurate diagnostic for GEPNEN and BPNEN. It exhibits tumor biology correlation with grading, staging, and progression. CgA as a biomarker is significantly less accurate than NETest. The NETest has substantial clinical utility that can facilitate patient management.

Neuroendocrine Tumor Omic Gene Cluster Analysis Amplifies the Prognostic Accuracy of the NETest

BACKGROUND

The NETest is a multigene assay comprising 51 circulating neuroendocrine tumor (NET)-specific transcripts. The quotient of the 51-gene assay is based upon an ensemble of machine learning algorithms. Eight cancer hallmarks or "omes" (apoptome, epigenome, growth factor signalome, metabolome, proliferome, plurome, secretome, SSTRome) represent 29 genes. The NETest is an accurate diagnostic (>90%) test, but its prognostic utility has not been assessed. In this study, we describe the expansion of the NETest omic cluster components and demonstrate that integration amplifies NETest prognostic accuracy.

METHODS

Group 1: n = 222; including stable disease (SD, n = 146), progressive disease (PD, n = 76), and controls (n = 139). Group 2: NET Registry NCT02270567; n = 88; prospective samples (SD, n = 54; PD, n = 34) with up to 24 months follow-up. We used PubMed literature review, interactomic analysis, nonparametric testing, Kaplan-Meier survival curves, and χ2 analyses to inform and define the prognostic significance of NET genomic "hallmarks."

RESULTS

2020 analyses: In-depth analyses of 47 -NETest genes identified a further six omes: fibrosome, inflammasome, metastasome, NEDome, neurome, and TFome. Group 1 analysis: Twelve omes, excluding the inflammasome and apoptome, were significantly (p < 0.05, 2.1- to 8.2-fold) elevated compared to controls. In the PD group, seven omes (proliferome, NEDome, epigenome, SSTRome, neurome, metastasome, and fibrosome) were elevated (both expression levels and fold change >2) versus SD. Group 2 analysis: All these seven omes were upregulated. In PD, they were significantly more elevated (p < 0.02) than in SD. The septet omic expression exhibited a 69% prognostic accuracy. The NETest alone was 70.5% accurate. A low NETest (≤40) integrated with epigenome/metastasome levels was an accurate prognostic for PD (90%). A high NETest (>40) including the fibrosome/NEDome predicted PD development within 3 months (100%). Using decision tree analysis to integrate the four omes (epigenome, metastasome, fibrosome, and NEDome) with the NETest score generated an overall prognostic accuracy of 93%.

CONCLUSIONS

Examination of NETest omic gene cluster analysis identified five additional clinically relevant cancer hallmarks. Identification of seven omic clusters (septet) provides a molecular pathological signature of disease progression. The integration of the quartet (epigenome, fibrosome, metastasome, NEDome) and the NETest score yielded a 93% accuracy in the prediction of future disease status.

The Challenge of Evaluating Response to Peptide Receptor Radionuclide Therapy in Gastroenteropancreatic Neuroendocrine Tumors: The Present and the Future

The NETTER-1 study has proven peptide receptor radionuclide therapy (PRRT) to be one of the most effective therapeutic options for metastatic neuroendocrine tumors (NETs), improving progression-free survival and overall survival. However, PRRT response assessment is challenging and no consensus on methods and timing has yet been reached among experts in the field. This issue is owed to the suboptimal sensitivity and specificity of clinical biomarkers, limitations of morphological response criteria in slowly growing tumors and necrotic changes after therapy, a lack of standardized parameters and timing of functional imaging and the heterogeneity of PRRT protocols in the literature. The aim of this article is to review the most relevant current approaches for PRRT efficacy prediction and response assessment criteria in order to provide an overview of suitable tools for safe and efficacious PRRT.

The NETest liquid biopsy is diagnostic for gastric neuroendocrine tumors: observations on the blood-based identification of microscopic and macroscopic residual diseaseOK

Background

NETest, a novel multi-gene liquid biopsy has utility in neuroendocrine tumor (NET) diagnosis and identification of residual disease. We independently assessed utility of the NETest to diagnose gastric neuroendocrine neoplasms (GNENs) and identify micro- and macroscopic residual disease.

Methods

Cohorts comprised histologically confirmed GNENs at biopsy, n = 46; GNETs Type 1: 42 (32 NET G1, 10 NET G2), a GNET Type 3: 1 well-differentiated NET G3, neuroendocrine carcinomas (NECs) (n = 3), and controls (n = 63). Disease status at sampling was assessed by gastroscopy, histology (resection margin [R] positivity of polypectomy or biopsy), EUS, CT or MRI, and/or ⁶⁸Ga-DOTA-TATE PET/CT. Groups included image- (gastroscopy, EUS, and anatomical and/or functional imaging) positive or image negative disease. NETest assay by PCR (spotted plates, normal cut-off: 20). Data: mean ± SD.

Results

Disease extent: Image-negative (n = 30) (21 R0, 9 R1); Image-positive, n = 16.

Diagnosis: NETest was increased in GNETs (23 ± 11) vs. controls (7 ± 4, p < 0.0001). In histology-positive, the NETest accuracy was 100% (25/25).

Microscopic disease: In image-negative but R1, NETest was elevated in 100% (9/9; 28 ± 9). Levels were elevated vs. controls (7 ± 4, p < 0.0001), or R0 (16 ± 11, p = 0.02). Eight of 21 R0, exhibited positive NETest.

Macroscopic disease: Gastric lesions were multiple: 38%, single: 62%, submucosal: 13%, or ulcerated: 13%. Lesions size was ≤5 mm (50%), > 5–9.9 mm (17%), 10–19.9 mm (17%), ≥20 mm (17%) [≥10 mm: 34%). The NETest accuracy was 100% (16/16). Levels (28 ± 7) were higher than controls (7 ± 4, p < 0.0001) or R0 (16 ± 11, p = 0.002) but not to R1 (28 ± 9, p = 0.5).

Conclusions

NETest is diagnostic for gastric NETs. Elevated levels identify both microscopic and macroscopic residual disease. In histology/image-negative disease, elevated NETest may reflect early evidence of increased neuroendocrine gene expression of hypergastrinemia-induced neoplastic transformation of enterochromaffin-like (ECL) cells to tumor status. A sensitive liquid biopsy has utility in the management and surveillance of gastric NET disease.